C
Senior Data Engineer - Databricks
Sydney, New South Wales, Australia · Full Time
Be the first to apply
- Experience
- 4+ yrs
- Salary
- —
- Openings
- 1
- Posted
- 13 seconds ago
- Work mode
- In office
- Resume
- Required to apply
Where you'll work
Sign in to tell us what does and doesn't work for you here — it sharpens every match we show you.
Job description
Role Overview
We are looking for an experienced Senior Data Engineer skilled in data engineering with a strong focus on Databricks, PySpark, Scala-Spark, and advanced SQL. The position involves working on data pipeline development, migration projects to Databricks Unity Catalog, performance tuning, and orchestration of workflows with modern data tools.
Key Responsibilities
- Deliver data engineering and analytics projects with a minimum of four years of experience.
- Lead or participate in at least one migration project to Databricks from platforms like Hadoop, Teradata, Oracle, or Talend.
- Design, develop, and enhance ETL workflows and data pipelines using Databricks and Apache Spark frameworks.
- Optimize Spark performance on Databricks for efficient data processing and management.
- Formulate and validate data delivery for large-scale Big Data initiatives.
- Collaborate with multiple teams to define and implement robust data solutions that satisfy organizational needs.
- Perform complex query tuning and optimize data models to improve performance.
- Orchestrate data workflows using tools such as Databricks Workflow, Azure Data Factory, Apache Airflow, or AWS Glue.
- Ensure data governance, security, and quality standards are upheld throughout the data lifecycle.
Technical Requirements
- Advanced proficiency in PySpark and Scala-Spark development.
- Strong expertise in writing advanced SQL queries for complicated data transformations.
- Proven track record optimizing Databricks Spark performance in at least three projects.
- Experience validating data formulations and deliveries specific to Big Data projects.
- Practical experience with at least two orchestration platforms among Databricks Workflow, Azure Data Factory, Apache Airflow, and AWS Glue.
Preferred Skills and Knowledge
- Familiarity with major cloud providers like AWS, Azure, or Google Cloud Platform.
- Understanding of data governance frameworks and security best practices.
- Additional experience with other Big Data technologies and frameworks is advantageous.
Skills
Tools & software
Apache Spark
required
Apache Airflow
required
Databricks
required